Publications citing Heart Murmur Detection from Phonocardiogram Recordings: The George B. Moody PhysioNet Challenge 2022 v1.0.0

Perspectives on Artificial Intelligence Enabled Heart Sound Analysis for Cardiac Amyloidosis
Tanisha Jindal, Jay Gohri, Vardhan Chalasani et al. Medical Sciences, 2026. Cites: paper

HM-Swin: Hierarchical Multiscale Swin Transformer Network with Attention Fusion for Heart Sound Classification
Kalpeshkumar Ranipa, Wei-Ping Zhu, M.N.S. Swamy. Bioengineering, 2026. Cites: paper

SDCNet: A Shapley-guided dynamic convolutional network for heart disease diagnosis with multi-site heart sounds
Jialei Yan, Hongbo Yang, Tao Guo et al. Information Sciences, 2026. Cites: paper

Multimodal AI estimates hemodynamic echocardiographic indicators of structural heart disease from heart sounds and pulse waves
Qun Wei, Incheol Kim, Ji-Seung Han et al. Research Square, 2026. Cites: paper

Multi-feature fusion with bidirectional cross-modal attention for joint multi-task classification of heart sounds
Yikang Zhang, Yanan Zhou, Yuwen Li et al. Medical & Biological Engineering & Computing, 2026. Cites: paper

MTENet: A Multi-Representation Time-Series Evidential Network for Automated Heart Murmur Detection from Phonocardiogram Signals
Yiğit Can Polat, Kenan Zengin. Applied Sciences, 2026. Cites: paper

Enhancing pediatric cardiac auscultation with data-driven murmur detection: toward tele-consultation applications
Raffaele Malvermi, Savina Mannarino, Vittoria Garella et al. Pediatric Research, 2026. Cites: paper

A deep learning-based non-contact phonocardiogram measurement method using mmWave radar
Haozhe Liu, Qilin Zhou, Xianglong Zhan et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Exploring Exertion-Aware AI Auscultation: Addressing Exercise-Induced Murmurs to Reduce False Pathological Alerts
Yixin Zhang, Shaaf Ahmad, Faisal F. Syed et al. IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, 2026. Cites: paper

Dual warm-start fusion versus attention-based fusion in low-label ECG–PCG classification: a controlled ablation study
Erkan Kıymık. Physiological Measurement, 2026. Cites: paper

Recent Advances in Deep Learning for Phonocardiogram Signal Analysis
Yuting Zeng, Yao Chen, You Wu et al. International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC), 2026. Cites: paper

A Prospective Real-Time Subspace KNN Ensemble for Heart Murmur Detection
Md. Iqbal Hossen Ashik, Hasibul Hasan Asif, Sharmin Jahan et al. IEEE International Conference on Quantum Photonics, Artificial Intelligence & Networking (QPAIN), 2026. Cites: paper

Detection of Cardiovascular Abnormalities With Heart Sounds Using Machine Learning
Syed Asrar Zahoor, KV Kiran Kumar, G Paramesh. International Conference on AI-Driven Innovations & Applications (IC-AIDA), 2026. Cites: paper

A self-Supervised ConvNeXt (SCONE) framework for robust and interpretable heart sound classification
M. Gayathri, Jogendra Kumar, Chandu Jagan Sekhar Madala et al. Intelligence-Based Medicine, 2026. Cites: paper

Automated detection of Chagas disease from ECG signals using wavelet scattering transform and RUSBoost classifier
Shivnarayan Patidar. Physiological Measurement, 2026. Cites: paper

Scattering Transformer: A Training-Free Transformer Architecture for Heart Murmur Detection
Rami Zewail. Lecture notes in computer science, 2026. Cites: paper

When and How to Focus: A Task-Dependent Analysis of Efficient Attentive Architectures for Biosignal Classification
Rami Zewail. IEEE Access, 2026. Cites: paper

H-LDM: Hierarchical Latent Diffusion Models for Controllable and Interpretable PCG Synthesis from Clinical Metadata
Chenyang Xu, Siming Li, Hao Wang. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

Heart Murmur Detection in Phonocardiogram Data Leveraging Data Augmentation and Artificial Intelligence
Melissa Valaee, Shahram Shirani. Diagnostics, 2025. Cites: paper

Deep learning based murmur detection from PCG signals collected at four valve locations using joint optimization and decision fusion
Monjur Morshed, Shaikh Anowarul Fattah. Results in Engineering, 2025. Cites: paper

Physical reservoir computing for biomedical applications
Yuqi Ding, Bhavani Prasad Yalagala, Haobo Li et al. Neuromorphic Computing and Engineering, 2025. Cites: paper

Assessing the Utility of Audio Foundation Models for Heart and Respiratory Sound Analysis
Daisuke Niizumi, Daiki Takeuchi, Masahiro Yasuda et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025. Cites: paper

Temporal convolutional neural network-based feature extraction and asynchronous channel information fusion method for heart abnormality detection in phonocardiograms
Jae-Man Shin, Seongyong Park, Keewon Shin et al. Computer Methods and Programs in Biomedicine, 2025. Cites: paper

Heart Murmur Detection and Clinical Outcome Prediction with a Hybrid Deep Learning Model using Phonocardiogram Recordings
Ehsan Karegar Foroogh, Amirhosein Zobeiri, Farshid Hajati et al. International Conference on Medical and Health Informatics (ICMHI), 2025. Cites: paper

A Deep-Learning Approach to Heart Sound Classification Based on Combined Time-Frequency Representations
Leonel Orozco-Reyes, Miguel Alonso, Eloísa García–Canseco et al. Technologies, 2025. Cites: paper

Exploring finetuned audio-LLM on heart murmur features
Adrian Nicolas Florea, Xilin Jiang, Nima Mesgarani et al. Smart Health, 2025. Cites: paper

A Flexible Multi-Sensor Device Enabling Handheld Sensing of Heart Sounds by Untrained Users
Andrew McDonald, Maximilian Nussbaumer, Nirmani Rathnayake et al. IEEE Journal of Biomedical and Health Informatics, 2025. Cites: paper

A Unified Joint Contrastive Triplet Loss with Temporal and Frequency Signal Fusion for Diagnosing Heart Murmurs
Ayushi Pal, Arka Roy, Udit Satija. IEEE International Conference on Acoustics Speech and Signal Processing, 2025. Cites: paper

AuscMLLM: Bridging Classification and Reasoning in Heart Sound Analysis with a Multimodal Large Language Model
Zihan Zhao, Pingjie Wang, Liudan Zhao et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2025. Cites: paper

Valve Token Masked Autoencoder for Missing Recordings on Cardiac Abnormality Classification
An-Yan Chang, Jing-Tong Tzeng, Huanyu Chen et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2025. Cites: paper

AI-Enhanced Detection of Heart Murmurs: Advancing Non-Invasive Cardiovascular Diagnostics
Maria-Alexandra Zolya, Elena-Laura Popa, Cosmin Baltag et al. Sensors, 2025. Cites: paper

Heart Murmur and Abnormal PCG Detection via Wavelet Scattering Transform and 1D-CNN
Ahmed Patwa, Muhammad Mahboob Ur Rahman, Tareq Y. Al-Naffouri. IEEE Sensors Journal, 2025. Cites: paper

Enhancement of phonocardiogram segmentation using convolutional neural networks with Fourier transform module
Changhyun Park, Keewon Shin, Jinew Seo et al. Biomedical Engineering Letters, 2025. Cites: paper

Digitalomics: Towards Artificial Intelligence / Machine Learning-Based Precision Cardiovascular Medicine
Akihiro Nomura, Yasuaki Takeji, Masaya Shimojima et al. Circulation Journal, 2025. Cites: paper

Case Studies in AI-Enhanced Diagnostics
Takanobu Hirosawa. Springer eBooks, 2025. Cites: paper

Denoising of Heart Sounds Using Lightweight FCNs and Spectrograms With and Without Context
Declan Duggan, Andriy Temko, Volodymyr Sarana et al. IEEE Access, 2025. Cites: paper

Remote Monitoring of Vital Signs
Stefania Cristina, Peter Počta, Andrej Žgank et al. Intelligent systems reference library, 2025. Cites: paper

Machine learning based heart murmur detection and classification
Ishan Fernando, D. Oliver Kannangara, Santhusha Kodituwakku et al. Biomedical Physics & Engineering Express, 2024. Cites: paper

pyPCG: a Python toolbox specialized for phonocardiography analysis
Kristóf Müller, Janka Hatvani, Miklós Koller et al. Physiological Measurement, 2024. Cites: paper

A recurrent neural network and parallel hidden Markov model algorithm to segment and detect heart murmurs in phonocardiograms
Andrew McDonald, Mark Gales, Anurag Agarwal. PLOS Digital Health, 2024. Cites: paper

Enhancing cross-domain robustness in phonocardiogram signal classification using domain-invariant preprocessing and transfer learning
Arnab Maity, Goutam Saha. Computer Methods and Programs in Biomedicine, 2024. Cites: paper

External evaluation of a commercial artificial intelligence-augmented digital auscultation platform in valvular heart disease detection using echocardiography as reference standard
Valentina Roquemen-Echeverri, Peter G. Jacobs, Evan Foster Shalen et al. International Journal of Cardiology, 2024. Cites: paper

Phonocardiogram (PCG) Murmur Detection Based on the Mean Teacher Method
Yi Luo, Zhongtao Fu, Yantian Ding et al. Sensors, 2024. Cites: paper

Demographic reporting in biosignal datasets: a comprehensive analysis of the PhysioNet open access database
Sarah Jiang, Perisa Ashar, Md Mobashir Hasan Shandhi et al. The Lancet Digital Health, 2024. Cites: paper

Transformers in biosignal analysis: A review
Ayman Anwar, Yassin Khalifa, James L. Coyle et al. Information Fusion, 2024. Cites: paper

Rapid detection and interpretation of heart murmurs using phonocardiograms, transfer learning and explainable artificial intelligence
Fatma Özcan. Health Information Science and Systems, 2024. Cites: paper

A deep neural network approach to heart murmur detection using spectrogram and peak interval features
Soyul Han, Taein Kang, Jungguk Lee et al. Engineering Applications of Artificial Intelligence, 2024. Cites: paper

Review of Phonocardiogram Signal Analysis: Insights from the PhysioNet/CinC Challenge 2016 Database
Bing Zhu, Zihong Zhou, Shaode Yu et al. Electronics, 2024. Cites: paper

Heart Murmur Quality Detection Using Deep Neural Networks with Attention Mechanism
Tingwei Wu, Zhaohan Huang, Shilong Li et al. Applied Sciences, 2024. Cites: paper

Development of a Tremor Detection Algorithm for Use in an Academic Movement Disorders Center
Mark Saad, Sofia Hefner, Suzann Donovan et al. Sensors, 2024. Cites: paper

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